Automated Recognition of RNA Structure Motifs by Their SHAPE Data Signatures.

ABSTRACT: High-throughput structure profiling (SP) experiments that provide information at nucleotide resolution are revolutionizing our ability to study RNA structures. Of particular interest are RNA elements whose underlying structures are necessary for their biological functions. We previously introduced patteRNA, an algorithm for rapidly mining SP data for patterns characteristic of such motifs. This work provided a proof-of-concept for the detection of motifs and the capability of distinguishing structures displaying pronounced conformational changes. Here, we describe several improvements and automation routines to patteRNA. We then consider more elaborate biological situations starting with the comparison or integration of results from searches for distinct motifs and across dat

SUBMITTER: Radecki P 

PROVIDER: S-EPMC6027059 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature